schedule

Determine an optimal charging/discharging schedule for each charger

Description

schedule determines an optimal charging/discharging schedule for each charger under a specific scenario.

out = schedule(scenario,algorithm_type)
out = schedule(scenario,algorithm_type,Name=Value)

Name	Type	Description
`scenario`	Scenario object	Scenario object that specifies the optimization problem
`algorithm_type`	“cent” \| “dist”	Type of algorithm, either “cent” for centralized or “dist” for distributed algorithm

Name	Type	Description
`rho`	5000 (default) \| nonnegative scalar	Penalty parameter
`Lf_kP`	1 (default) \| positive scalar	Coupling gain (proportional) for distributed PI algorithm (Only for “dist”)
`Lf_kI`	1 (default) \| positive scalar	Coupling gain (integral) for distributed PI algorithm (Only for “dist”)
`Lf_time`	400 (default) \| positive scalar	Length of time interval on which PI dynamics is executed (Only for “dist”)
`Lf_dt`	0.0005 (default) \| positive scalar	Stepsize for the Euler discritization of PI dynamics (Only for “dist”)
`Lf_scale`	0.05 (default) \| positive scalar	Cost function scaling factor for PI dynamics (Only for “dist”)
`Uf_iteration`	40 (default) \| positive integer	Number of iterations for the distributed algorithm (Only for “dist”)
`Uf_K`	30 (default) \| positive integer	Number of fractional iterations for the distributed algorithm (Only for “dist”)
`Uf_c`	0.1 (default) \| positive scalar	Parameter for the distributed algorithm (Only for “dist”)
`Uf_theta`	0 (default) \| scalar	Parameter for the distributed algorithm (Only for “dist”)
`quiet`	false (default) \| logical	On/off solver messages

Name	Type	Description
`out`	struct	Results including charging schedules, cost, solved scenario, etc.